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Record W3085515340 · doi:10.1093/bjsw/bcaa128

Epistemology, Social Work and Substance Use

2020· article· en· W3085515340 on OpenAlexaff
Sandra McNeil

Bibliographic record

VenueThe British Journal of Social Work · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPositivismSociologyEpistemologyViewpointsSocial workSocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract Social work and substance use research often neglect to make epistemological perspectives explicit in their studies, inadvertently embedding numerous assumptions that remain invisible and uncontested. Consequently, the unchallenged dominance of post-positivist epistemologies in Western European countries becomes (re)produced in social work and substance use education, policies and practices, limiting space for alternative viewpoints. This narrative review examines some of the social work and substance use literature, highlighting the value of making epistemology more explicit and the importance of applying critical epistemologies to counter dominant paradigms. This article makes a unique contribution to substance use literature by examining substance use from post-positivist, social constructivist and critical paradigms and by promoting a critical social work lens. A critical paradigm is particularly useful for questioning prevailing assumptions of substance use as a medical problem requiring professional treatment and for generating greater attention to structural policies that promote a more equitable society. Social work’s commitment to human rights and social justice effectively positions the discipline to apply a critical paradigm to the field of substance use studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.208
GPT teacher head0.387
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2020
Admission routes1
Has abstractyes

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